3 citations · 4 across the 6 of their papers we have counts for
6 papers
AR as an Evaluation Playground: Bridging Metrics and Visual Perception of Computer Vision Models
Ashkan Ganj, Yiqin Zhao, Tian Guo
Quantitative metrics are central to evaluating computer vision (CV) models, but they often fail to capture real-world performance due to protocol inconsistencies and ground-truth n…
HybridDepth: Robust Metric Depth Fusion by Leveraging Depth from Focus and Single-Image Priors
Ashkan Ganj, Hang Su, Tian Guo
We propose HYBRIDDEPTH, a robust depth estimation pipeline that addresses key challenges in depth estimation,including scale ambiguity, hardware heterogeneity, and generalizability…
Mobile AR Depth Estimation: Challenges & Prospects -- Extended Version
Ashkan Ganj, Yiqin Zhao, Hang Su +1
Metric depth estimation plays an important role in mobile augmented reality (AR). With accurate metric depth, we can achieve more realistic user interactions such as object placeme…
Get-A-Sense: Designing Spatial Context Awareness for Mobile AR Environment Understanding
Yiqin Zhao, Ashkan Ganj, Tian Guo
Physical environment understanding is vital in delivering immersive and interactive mobile augmented reality (AR) user experiences. Recently, we have witnessed a transition in the…
Toward Scalable and Controllable AR Experimentation
Ashkan Ganj, Yiqin Zhao, Federico Galbiati +1
To understand how well a proposed augmented reality (AR) solution works, existing papers often conducted tailored and isolated evaluations for specific AR tasks, e.g., depth or lig…
LR-Net: A Block-based Convolutional Neural Network for Low-Resolution Image Classification
Ashkan Ganj, Mohsen Ebadpour, Mahdi Darvish +1
The success of CNN-based architecture on image classification in learning and extracting features made them so popular these days, but the task of image classification becomes more…